第二版

Question

我是opencv的新手，对于一个学校项目，我需要用相机检测红色和绿色圆圈，所以我使用blobdetection，但它检测到我的两种颜色，我认为我的面具很糟糕，每种颜色都与特定动作相关联。

目前我的代码在同一页面上检测到红色和绿色的圆圈，但我希望它只检测白页上的红色圆圈。

感谢您的帮助

# Standard imports
import cv2
import numpy as np;

    # Read image
im = cv2.VideoCapture(0)

# Setup SimpleBlobDetector parameters.
params = cv2.SimpleBlobDetector_Params()

# Change thresholds
params.minThreshold = 100;
params.maxThreshold = 200;

# Filter by Area.
params.filterByArea = True
params.minArea = 200
params.maxArea = 20000

# Filter by Circularity
params.filterByCircularity = True
params.minCircularity = 0.1

# Filter by Convexity
params.filterByConvexity = True
params.minConvexity = 0.1

# Filter by Inertia
params.filterByInertia = True
params.minInertiaRatio = 0.1


blueLower = (0,85,170)  #100,130,50
blueUpper = (140,110,255) #200,200,130


while(1):

    ret, frame=im.read()

    mask = cv2.inRange(frame, blueLower, blueUpper)
    mask = cv2.erode(mask, None, iterations=0)
    mask = cv2.dilate(mask, None, iterations=0)
    frame = cv2.bitwise_and(frame,frame,mask = mask)

# Set up the detector with default parameters.
    detector = cv2.SimpleBlobDetector_create(params)

# Detect blobs.
    keypoints = detector.detect(mask)

# Draw detected blobs as red circles.
# cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS ensures the size of the circle corresponds to the size of blob
    im_with_keypoints = cv2.drawKeypoints(mask, keypoints, np.array([]), (0,0,255), cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)


# Display the resulting frame

    frame = cv2.bitwise_and(frame,im_with_keypoints,mask = mask)

    cv2.imshow('frame',frame)

    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# When everything done, release the capture
im.release()
cv2.destroyAllWindows()

编辑1：代码更新

现在我遇到了一个未检测到完整圆圈的问题。

No Blob Detection

第二版

# Standard imports
import cv2
import numpy as np;

# Read image
im = cv2.VideoCapture(0)

while(1):
        ret, frame=im.read()


        lower = (130,150,80)  #130,150,80
        upper = (250,250,120) #250,250,120
        mask = cv2.inRange(frame, lower, upper)
        lower, contours, upper = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
        blob = max(contours, key=lambda el: cv2.contourArea(el))
        M = cv2.moments(blob)
        center = (int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"]))
        canvas = im.copy()
        cv2.circle(canvas, center, 2, (0,0,255), -1)

        cv2.imshow('frame',frame)

        if cv2.waitKey(1) & 0xFF == ord('q'):
                break
im.release()
cv2.destroyAllWindows()

Answer 1

你需要弄清楚你的果岭的BGR数字是什么（让我们为了论证[0, 255, 0]而说），然后创建一个遮挡绿色周围公差之外的任何颜色的面具：

mask = cv2.inRange(image, lower, upper)

逐步查看this教程。

使用较低和较高的游戏来获得正确的行为。然后你可以在面具中找到轮廓：

_, contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, 
                                                    cv2.CHAIN_APPROX_NONE)

然后浏览contours列表找到最大的一个（过滤掉任何可能的噪音）：

blob = max(contours, key=lambda el: cv2.contourArea(el))

那是你的最后一次＆＃39;。您可以通过以下方式找到该中心：

M = cv2.moments(blob)
center = (int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"]))

您可以将此中心绘制到图像的副本上，以便进行检查：

canvas = im.copy()
cv2.circle(canvas, center, 2, (0,0,255), -1)

显然，这假设图像中只有一个绿球而没有其他绿色。但这是一个开始。

编辑 - 对第二次发布的回复

我认为以下内容应该有效。我还没有对它进行过测试，但你应该至少可以使用画布和掩码进行更多调试：

# Standard imports
import cv2
import numpy as np;

# Read image
cam = cv2.VideoCapture(0)

while(1):
        ret, frame = cam.read()

        if not ret:
            break

        canvas = frame.copy()


        lower = (130,150,80)  #130,150,80
        upper = (250,250,120) #250,250,120
        mask = cv2.inRange(frame, lower, upper)
        try:
            # NB: using _ as the variable name for two of the outputs, as they're not used
            _, contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
            blob = max(contours, key=lambda el: cv2.contourArea(el))
            M = cv2.moments(blob)
            center = (int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"]))

            cv2.circle(canvas, center, 2, (0,0,255), -1)

        except (ValueError, ZeroDivisionError):
            pass

        cv2.imshow('frame',frame)
        cv2.imshow('canvas',canvas)
        cv2.imshow('mask',mask)

        if cv2.waitKey(1) & 0xFF == ord('q'):
                break
im.release()
cv2.destroyAllWindows()

Answer 2

如果您想按颜色进行过滤，则应使用HSV颜色空间以获得更好的效果。

ret, frame=im.read()

frame = cv2.cvtColor（frame，cv2.COLOR_BGR2HSV）＃ 将此添加到您的代码中

mask = cv2.inRange(frame, blueLower, blueUpper)

检测不同颜色的blob opencv

第二版

2 个答案: